- Feng, Kun

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# Feng, Kun

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Feng, Kun

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Feng, Kun

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- PublicationExtraction of dynamic features from short acceleration data bursts: a reviewIt is well known that structural damage can lead to changes in dynamic features such as frequencies, mode shapes, damping, vibration intensity, etc. Signal processing tools available to extract these features include Wavelet analysis, Fourier and Hilbert-Huang transforms. Acceleration data is typically used as input to these tools, given that it is a type of response with a relatively high dynamic component (i.e., oscillations in the response due to inertial forces of the structure) in relation to the static component (i.e., derived from time-varying static deflections as a result of time/spatial-varying loads). Almost all traditional signal processing approaches require access to long-time data sets. For instance, long periods of acceleration and multiple measurement points allow engineers to accurately define the mode shapes of a structure. In this paper, a scenario is envisioned where drones are used to charge sensors placed on bridges as well as to acquire the data recorded by the sensors for processing. The novelty is the challenge of monitoring structural condition in the context of acquiring limited quantities of data. The latter requires being able to deal with a very significant impact of edge effects and the loss of resolution due to the short duration of the signal. This paper reviews attempts to obtain bridge dynamic features overcoming these limitations, i.e., via multi-stage measurements as in the case of the Short Time Frequency Domain Decomposition method.
198 - PublicationA numerical Investigation into the use of forced vibration due to Vehicular Loads for structural health monitoring of bridgesStructural Health Monitoring (SHM) aims to achieve early damage detection in bridges by characterizing changes in dynamic properties from the structural response acquired via sensors such as accelerometers. Currently, a new generation of SHM technologies is emerging to gather information in a low-cost and energy-efficient manner from the vibrations induced by vehicular loading. More specifically, the developments included in this thesis apply to technologies avoiding the need for a permanent installation on the bridge. They typically record measurements for a short duration of the response, which makes the limited info captured about the bridge highly sensitive to vehicular and road properties. The accelerometers can be placed on: (i) the bridge (i.e., direct measurements gathered through unmanned aerial vehicles), and (ii) the axles of a vehicle crossing the bridge (the so-called indirect measurements, or â€˜drive-byâ€™). Therefore, this thesis intends to detect, locate and quantify damage using short data bursts of forced vibration due to vehicular loading. Here, damage is understood as either a stiffness loss (global or local) or a deterioration of the support conditions. This research contributes to technologies based on location (i) by proposing an algorithm that relies on the measurements from an accelerometer during the forced vibration of the bridge while traversed by a specialised vehicle. The algorithm exploits the variation in bridge frequency, not only with the magnitude and location of the moving vehicle but also with the stiffness profile of the bridge. A k-Nearest Neighbours algorithm searches for the patterns of forced eigenfrequencies that are closest to the on-site instantaneous frequencies to determine the location and severity of the damage. The algorithm shows promising results, although it is limited to low vehicle speeds and low road roughness. Furthermore, this thesis contributes to the technology (ii) with three model-based drive-by algorithms, i.e., involving a finite element model of the bridge and a vehicular model, which are necessary to locate and quantify the damage. Three components can be distinguished within a measured vehicular acceleration: bridge, vehicle, and road components. The last two components usually govern the frequency spectrum, which makes it hard to distinguish the targeted bridge information. As a result, â€˜drive-byâ€™ solutions are often developed for damage detection purposes only, meaning that they rarely locate or quantify the damage, and when they do so, is usually under strict requirements, i.e., specific vehicle properties, low vehicular speed and smooth road profiles. In order to mitigate the undesired vehicle component, the concept of transfer function is applied to derive the response of the contact point between the vehicle and the bridge from the response of the acceleration of an axle. In order to deal with the road component, each algorithm uses a different strategy as follows: (1) estimation of the energy content in the frequency domain following the removal of the road profile in the spatial frequency domain based on measurements at different speeds. Damage is located and quantified by comparison to a database of responses generated via a simple P-load model; (2) optimisation of the road profiles estimated in the time domain using measurements in one axle at two different speeds. Based on cross-entropy optimization, the stiffness profile of a simply supported bridge model is accurately predicted, even for relatively high speeds and rough roads, except for locations next to the supports; (3) optimisation of the road profiles estimated in the time domain by two axles of the same vehicle. This algorithm addresses the condition of the bridge supports. Finally, drive-by algorithms (2) and (3) yield an accurate representation of the road profile on the bridge, in addition to an assessment of the mechanical properties of the bridge.
15 - PublicationNumerical analysis of techniques to extract bridge dynamic features from short records of accelerationThe use of drones in Structural Health Monitoring (SHM) to charge sensors mounted on a bridge and download their data has gathered interest over the last years. This approach presents the advantage of avoiding the need for long cables running over the bridge or for permanent access to electric power on site. Nonetheless, limitations exist regarding the amount of data that can be transmitted through this method. In contrast to traditional approaches to SHM relying on long records to assess the condition of a structure, the scenario envisioned here deals with short amounts of data. In this paper, specific methodologies for extraction of dynamic features from short data bursts of acceleration signal are tested through numerical simulations. The bridge is modelled as a simply supported finite element beam model that is excited by a series of moving concentrated forces, which represent a random traffic load. Initial conditions are varied allowing for scenarios in which the acceleration record may start once the vehicle is already on the bridge, finish before its exit or combine periods of free and forced vibration. The theoretical acceleration response is obtained for healthy and damage conditions of the bridge, and then corrupted with noise. Focus is placed on how effective these techniques are in overcoming the shortcuts derived from noise and from the short duration of the signal. Therefore, techniques to mitigate common problems such as mode-mixing and edge effects are investigated.
316 - PublicationImpact of short-duration acceleration records on the ability of signal processing techniques to derive accurate bridge frequenciesThis paper envisions a scenario in which unmanned aerial vehicles gather data from low-cost and flexible wireless sensor networks, i.e., accelerometers. However, flight duration, coupled with limited sensor battery time, is a substantial technical limitation. In order to assess the impact of these constraints on bridge monitoring, this paper analyses the extraction of bridge dynamic features from short-duration acceleration records. The short acceleration record is simulated using the theoretical response of a simply supported beam subjected to a moving load. Estimated frequencies are obtained in free vibration and compared with the natural frequencies calculated from formula. Given that short records limit the resolution in the frequency domain, the error in the prediction of frequencies will typically decrease as the duration of the signal increases. Signal processing techniques for extracting dynamic features include the Fast Fourier Transform, Frequency Domain Decomposition, Continuous Wavelet Transform and Hilbert-Huang Transform. This paper carries out an assessment of the accuracy of these signal processing techniques in extracting frequencies as a function of the duration of the measurements. Edge effects and loss of resolution are shown to remain key issues to be addressed when the duration of the signal is too short.
280 - PublicationLocalisation and quantification of stiffness loss based on the forced vibration of a beam traversed by a quarter-carThis paper proposes a method for locating and quantifying bridge damage based on the time-varying forced frequencies due to moving traffic. The vehicle-bridge coupled system is simplified using a quarter-car model and a simply supported beam. Eigenvalue analysis shows that the eigenfrequencies of the coupled system vary for different vehicle positions. If a local stiffness loss is introduced, the forced frequencies associated with the â€˜damageâ€™ scenario will differ from those of a reference â€˜healthyâ€™ scenario. The differences between both scenarios depend on the location and severity of damage as well as on the mass and frequency ratios between quarter-car and beam models. In practice, bridge acceleration due to the crossing of a vehicle can be measured and processed using a time-frequency signal processing tool to obtain instantaneous frequencies. Changes in local stiffness are determined from comparing those instantaneous frequencies with the eigenfrequencies based on the same bridge and vehicle configuration.
151ScopusÂ© Citations 1 - PublicationThe Use of the Forced Frequency of a Bridge Due to a Truck Fleet for Estimating Stiffness Losses at Low SpeedThe influence of traffic loads on the dynamic features of a bridge is an external factor that can hinder the true condition of the structure. This paper aims to effectuate a shift in the way this factor is viewed. If the interaction between vehicle and bridge is modeled using the finite element method, the response is based on mass, stiffness, and damping matrices of a coupled vehicle-bridge system that vary with the location of the load at each point in time. The time-varying forced frequencies of a beam bridge model due to a fleet of 3-axle trucks based on eigenvalue analysis (i.e., derived from the matrices of the coupled system) are compared to those obtained using dynamic transient analysis (i.e., derived from the frequency content of the acceleration response of the beam due to a truck crossing). Truck properties are randomly varied within a realistic range to obtain a pattern for the forced vibration due to a truck fleet traveling at an ideal speed of 1 m/s on a 15 m bridge with a smooth surface, and at 10 m/s on a 30 m bridge. These patterns reveal a trend that allows for locating and quantifying the stiffness loss associated with a crack using only the forced frequency. The implementation of this methodology requires the installation of accelerometers on the bridge, and a nearby weigh-in-motion system to identify the traffic fleet of interest. High requirements for frequency resolution limit the application to bridges located on low speed routes.
71ScopusÂ© Citations 3 - PublicationSensitivity to Damage of the Forced Frequencies of a Simply Supported Beam Subjected to a Moving Quarter-CarThe vibration of bridges under operational conditions can be measured via accelerometers to extract their dynamic features. These features can then be monitored in time, although only a reduced number of cause-effect scenarios can be verified on the field. Therefore, theoretical models of the bridge are often employed for covering a wider range of scenarios. For instance, a variety of damage conditions can be introduced in a calibrated bridge model to obtain the associated frequencies, which can be subsequently compared to frequencies measured on-site for assessing the bridge condition. It must be noted that these frequencies may be influenced by factors other than damage, i.e., environmental effects due to temperature changes and operational effects due to traffic. During the forced vibration of a bridge caused by a moving vehicle, the frequencies governing the bridge response depend on the mass and stiffness ratios of the vehicle to the bridge. Therefore, records in free vibration are usually preferred or alternatively, the influence of operational loads is removed from forced vibration records before assessing whether damage has occurred or not. This paper shows that forced vibration stores relevant information about damage beyond the frequency changes derived from free vibration. Eigenvalue analysis is employed to investigate how forced frequencies change with the positions of a crossing vehicle and damage. The vehicle is modelled using a quarter-car and the bridge as a simply supported finite element beam, where damage is introduced via localized stiffness losses.
333ScopusÂ© Citations 5 - PublicationThe use of accelerometers in UAVs for bridge health monitoringUnmanned Aerial Vehicles (UAVs) technology has gained considerable popularity in bridge structural health monitoring for its strengths, such as low cost, safety and high energy efficiency. This paper envisions a scenario in which accelerometers are mounted onto UAVs, which then are able to gather acceleration signals by self-attaching to the bridge. However, battery life is an issue in UAVs with the subsequent limitation in the duration of the measurements. Therefore, this paper carries out a simulation on mode shape extraction from a short data burst by utilising an output only technique, the so-called frequency domain decomposition (FDD). Modal assurance criterion (MAC) is used as a statistical indicator to check differences between the estimated mode shapes and the eigenvectors from finite element analysis. The short acceleration response is generated using a planar vehicle-bridge interaction system where the moving load is modelled as two quarter-cars and the bridge is modelled as a simply supported beam. The impact of signal noise, vehicle speed and signal duration on the accuracy of the estimated mode shapes is investigated. FDD is shown to achieve high values of MAC even for short data bursts. Damping ratio is identified as a significant source of MAC discrepancy in the extraction of mode shapes. The stiffness loss due to a crack is introduced in the beam to evaluate how damage affects the mode shape compared to operational effects. How the MAC values vary with crack location and damage severity is discussed for the first three mode shapes.
204 - PublicationModal analysis of a bridge using short-duration accelerations(2019-08-07)
; ; The application of unmanned aerial vehicle technology to bridge structural health monitoring has become a hot research topic due to its low cost, safety and high energy efficiency. However, flight duration and battery life are substantial technical limitations. Is a short data burst sufficient for damage detection? This paper intends to answer this question by developing a novel approach based on frequency domain decomposition to obtain the mode shapes from a short data burst. Then, the modal assurance criterion is used as an indicator of the differences between the estimated mode shapes from the short data burst and the exact eigenvectors from finite element analysis. Here, the short data burst is obtained from the simulated acceleration response of a bridge beam model due to the crossing of two quarter-cars. A new damage indicator based on the modal assurance criterion profile along the beam is proposed to locate and quantify damage.205